 Copyright 2011 Digital Enterprise Research Institute. All rights reserved. Digital Enterprise Research Institute Enabling Networked Knowledge Gephi Workshop 1 David Crowley Maciej Dabrowski

Digital Enterprise Research Institute Enabling Networked Knowledge Open Gephi  On the lab machines it might have to “install” or “download” it but should only take 2-3 mins We are going to play with the “Les-Miserables.gexf” sample file to start Save a copy so you can always start again with the original file

Digital Enterprise Research Institute Enabling Networked Knowledge Change to Directed

Digital Enterprise Research Institute Enabling Networked Knowledge

Digital Enterprise Research Institute Enabling Networked Knowledge Les Miserables Network Co-appearance weighted network of characters in the novel “Les Miserables” from Victor Hugo. Nodes are placed randomly so it may look different for you

Digital Enterprise Research Institute Enabling Networked Knowledge Controls

Digital Enterprise Research Institute Enabling Networked Knowledge Layouts Layout algorithms sets the graph shape, it is the most “essential action” (for visualising) Graphs are usually layouted with “Force- based” algorithms. Their principle is easy, linked nodes attract each other and non-linked nodes are pushed apart Layout Panel  Shows layout choice  And Layout Properties

Digital Enterprise Research Institute Enabling Networked Knowledge Force Atlas 2 Run the layout for a few seconds and press stop You should end up with a graph like this (not exactly the same or it could even be quite different)

Digital Enterprise Research Institute Enabling Networked Knowledge Layout Properties The purpose of Layout Properties is to let you control the algorithm in order to make a aesthetically pleasing representation Change Scaling (repulsion) to a high number and see what happens and then make it small Each time we need to run and stop the layout before any visible change happens.

Digital Enterprise Research Institute Enabling Networked Knowledge Layout with 50

Digital Enterprise Research Institute Enabling Networked Knowledge Ranking Choose Ranking on the Right Hand Side panel above the layout panel Nodes should be selected In the drop down menu you should have three options  Degree  Indegree  Outdegree

Digital Enterprise Research Institute Enabling Networked Knowledge Ranking Choose Degree Click Apply Now your graph should be coloured in You can change the colour settings by clicking on the colour bar

Digital Enterprise Research Institute Enabling Networked Knowledge Result List Click on Result List as highlighted by the red arrow Click Apply Now you should see the nodes listed by Rank

Digital Enterprise Research Institute Enabling Networked Knowledge Metrics We will calculate the average path length for the network. It computes the path length for all possibles pairs of nodes and give information about how nodes are close from each other

Digital Enterprise Research Institute Enabling Networked Knowledge Choose Directed – Click OK

Digital Enterprise Research Institute Enabling Networked Knowledge Results

Digital Enterprise Research Institute Enabling Networked Knowledge Ranking In the Ranking Panel now in Nodes, we have more metrics Every (or almost every time) you run a metric you add a new way to rank the graph

Digital Enterprise Research Institute Enabling Networked Knowledge Ranking (size) with overlap turned off

Digital Enterprise Research Institute Enabling Networked Knowledge Community Detection (Modularity) Community Detection – used a lot! Can we predict collapse of online communities? Concept of hubs – key points in the network Crime networks – old studies on white collar crime

Digital Enterprise Research Institute Enabling Networked Knowledge Modularity Run modularity Now you can rank nodes by modularity This should identify “communities”

Digital Enterprise Research Institute Enabling Networked Knowledge Partition If you click on Partition (next to Ranking) Press Refresh You can partition by Modularity Class

Digital Enterprise Research Institute Enabling Networked Knowledge Filters You can run Filters on your graph Useful for large graphs Finds components or hides components